Mechanistic links between gut microbial community dynamics, microbial functions and metabolic health

作     者：Connie WY Ha Yan Y Lam Andrew J Holmes 

作者机构：School of Molecular Bio-science and Charles Perkins Centre The University of Sydney Pennington Biomedical Research Center 

出 版 物：《World Journal of Gastroenterology》 (世界胃肠病学杂志（英文版）)

年 卷 期：2014年第20卷第44期

页      面：16498-16517页

核心收录：

学科分类：1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

主　　题：Microbiome Dysbiosis High fat diet Bile Intestinal mucosa Microbe-associated molecular patterns Short chain fatty acids Immunomodulation Enteroendocrine cells 

摘      要：Gut microbes comprise a high density, biologically active community that lies at the interface of an animal with its nutritional environment. Consequently their activity profoundly influences many aspects of the physiology and metabolism of the host animal. A range of microbial structural components and metabolites directly interact with host intestinal cells and tissues to influence nutrient uptake and epithelial health. Endocrine, neuronal and lymphoid cells in the gut also integrate signals from these microbial factors to influence systemic responses. Dysregulation of these host-microbe interactions is now recognised as a major risk factor in the development of metabolic dysfunction. This is a two-way process and understanding the factors that tip host-microbiome homeostasis over to dysbiosis requires greater appreciation of the host feedbacks that contribute to regulation of microbial community composition. To date, numerous studies have employed taxonomic profiling approaches to explore the links between microbial composition and host outcomes(especially obesity and its comorbidities), but inconsistent host-microbe associations have been reported. Available data indicates multiple factors have contributed to discrepancies between studies. These include the high level of functional redundancy in host-microbiome interactions combined with individual variation in microbiome composition; differences in study design, diet composition and host system between studies; and inherent limitations to the resolution of r RNA-based community profiling. Accounting for these factors allows for recognition of the common microbial and host factors driving community composition and development of dysbiosis on high fat diets. New therapeutic intervention options are now emerging.